Modern time-of-flight (TOF) systems can ascertain depth distances (Z) to a target object by emitting modulated optical energy of a known phase (φ), and examining phase-shift in the optical signal reflected from the target object back to the TOF system. Exemplary such phase-type TOF systems are described in several U.S. patents received by Canesta, Inc., and now assigned to Microsoft, Inc. Such patents include U.S. Pat. Nos. 6,515,740 “Methods for CMOS-Compatible Three-Dimensional Imaging Sensing Using Quantum Efficiency Modulation”, 6,906,793 entitled Methods and Devices for Charge Management for Three Dimensional Sensing, 6,678,039 “Method and System to Enhance Dynamic Range Conversion Useable With CMOS Three-Dimensional Imaging”, 6,587,186 “CMOS-Compatible Three-Dimensional Image Sensing Using Reduced Peak Energy”, 6,580,496 “Systems for CMOS-Compatible Three-Dimensional Image Sensing Using Quantum Efficiency Modulation”.
As the present invention is used with such prior art phase-type TOF systems, it is useful at this juncture to review their operation. FIG. 1A is based upon the above-referenced patents, e.g. the '186 patent, and depicts an exemplary phase-type TOF system.
In FIG. 1A, exemplary phase-shift TOF depth imaging system 100 may be fabricated on an IC 110 that includes a two-dimensional array 130 of pixel detectors 140, which pixel detectors may be single-ended or differential in operation. Preferably each of the pixel detectors 140 has dedicated circuitry 150 for processing detection charge output by the associated detector. IC 110 preferably also includes a microprocessor or microcontroller unit 160, memory 170 (which preferably includes random access memory or RAM and read-only memory or ROM), a high speed distributable clock 180, and various computing and input/output (I/O) circuitry 190. Among other functions, controller unit 160 may perform distance to object and object velocity calculations.
Under control of microprocessor 160, optical energy source 120 is periodically energized by an exciter 115, and emits modulated optical energy toward an object target 20. Emitter 120 preferably is at least one LED or laser diode(s) emitting low power (e.g., perhaps 1 W) periodic waveform, producing optical energy emissions of known frequency (perhaps a few dozen MHz) for a time period known as the shutter time (perhaps 10 ms). Typically emitter 120 operates in the near IR, with a wavelength of perhaps 800 nm. A lens 125 is commonly used to focus the emitted optical energy.
Some of the emitted optical energy (denoted Sout) will be reflected (denoted Sin) off the surface of target object 20. This reflected optical energy Sin will pass through an aperture field stop and lens, collectively 135, and will fall upon two-dimensional array 130 of pixel or photodetectors 140. When reflected optical energy Sin impinges upon photodetectors 140 in array 130, photons within the photodetectors are released, and converted into tiny amounts of detection current. For ease of explanation, incoming optical energy may be modeled as Sin=A·cos(ω·t+θ), where A is a brightness or intensity coefficient, ω·t represents the periodic modulation frequency, and θ is phase shift. As distance Z changes, phase shift θ changes, and FIGS. 1B and 1C depict a phase shift θ between emitted and detected signals. The phase shift θ data can be processed to yield desired Z depth information. Within array 130, pixel detection current can be integrated to accumulate a meaningful detection signal, used to form a depth image. In this fashion, TOF system 100 can capture and provide Z depth information at each pixel detector 140 in sensor array 130 for each frame of acquired data.
Signal detection within phase-type TOF systems such as system 100 is described more fully later herein with respect to FIG. 2B, but in brief, pixel detection information is captured at least two discrete phases, preferably 0° and 90°, and is processed to yield Z data.
System 100 yields a phase shift θ at distance Z due to time-of-flight given by:θ=2·ω·Z/C=2·(2·π·f)·Z/C  (1)
where C is the speed of light, 300,000 Km/sec. From equation (1) above it follows that distance Z is given by:Z=θ·C/2·ω=θ·C/(2·2·f·π)  (2)And when θ=2·π, the aliasing interval range associated with modulation frequency f is given as:ZAIR=C/(2·f)  (3)
In practice, changes in Z produce change in phase shift θ but eventually the phase shift begins to repeat, e.g., θ=θ+2·π, etc. Thus, distance Z is known modulo 2·π·C/2·ω)=C/2·f, where f is the modulation frequency. Thus there can be inherent ambiguity between detected values of phase shift θ and distance Z, and multi-frequency methods are employed to disambiguate or dealias the phase shift data. Thus, if system 100 reports a distance Z1, in reality the actual distance may be any of ZN=Z1+N·C/2f, where N is an integer. The nature of this ambiguity may be better understood with reference to FIGS. 1D and 1E.
FIG. 1D is a mapping of detected phase θ versus distance Z for system 100. Assume that system 100 determines a phase angle θ′ for target object 20, where this phase information was acquired with a modulation frequency f1 of say 50 MHz. As shown by FIG. 1D, there are several distances, e.g., z1, z2, z4, z5, etc. that could be represented by this particular phase angle . . . but which is the correct distance? In FIG. 1D, ZAIR1 represents the Z distance aliasing interval range associated with z data acquired at frequency f1, and is the distance from z1 to z2, or z2 to z4, or z4 to z5, etc. These various z1, z2, z4, z5, distances are ambiguous and require disambiguation or dealiasing to identify the correct distance value. The terms disambiguate and dealias, or disambiguation and dealiasing, may be used interchangeably herein.
It is desired to dealias the z data by increasing magnitude of the aliasing interval range ZAIR1. One prior art approach does this by increasing the ratio C/2f, which is to say, by decreasing the modulation frequency f, see equation (3). FIG. 1D also shows, in bold line, phase data acquired for a lower modulation frequency f2. In FIG. 1D, f2 is perhaps 20 MHz, in that the slope dθ/dz for the f2 waveform is less than about half the slope for the f1 waveform, where the slope dθ/dz is proportional to modulation frequency fm. FIG. 1E is a polar representation in which a vector, depicted as a line rotating counter-clockwise, rotates with velocity ω=dθ/dt=2πf. In prior art system 100, data is captured from pixel detectors at least two discrete phases, e.g., 0° and 180°.
Thus in FIG. 1D, when the lower modulation frequency f2 is employed, the candidate distance values represented by phase θ′ are z3, z6, etc. As seen in FIG. 1D, the aliasing interval range ZAIR2 has advantageously increased from a short range ZAIR1 (associated with faster modulation frequency f1) to a greater range ZAIR2. The ratio of the aliasing interval range increase will be the ratio f2/f1. But acquiring phase data with lower modulation frequency f2 yields a Z value with less precision or resolution than if acquired with higher modulation frequency This imprecision occurs because the slope of the curve for frequency f2 is about half the slope for modulation frequency f1. Thus errors in the measurement of phase acquired at f2 translate to greater errors in Z than errors in phase acquired at f1. For the same signal/noise ratio, errors in phases acquired at f1 and at f2 will be the same, but the corresponding uncertainty errors in Z use phase acquired at the lower f2 modulation frequency will be about twice as large for the representation of FIG. 1D. Thus, all things being equal, lowering the modulation frequency undesirably results in lower resolution (greater uncertainty) in accurately determining Z.
Thus while increasing the aliasing range interval is desired, doing so by decreasing the modulation frequency f is not desirable. This modulation frequency decrease approach to dealiasing is wasteful since lower modulation frequency means lower pixel sensor 140 accuracy per watt of illumination power from emitter 120 (see FIG. 1A). For example, a reduction of modulation frequency by a factor of 2.5, say from f=50 MHz to f=20 MHz, will advantageously increase the aliasing interval by the same factor, e.g., from 3 m to 7.5 m, but the penalty is a substantial (2.5)·(2.5)=6.25× increase in operating power to achieve similar uncertainty performance, assuming effects of ambient sunlight can be ignored. By way of further example, if modulation frequencies of 50 MHz and 10 MHz were used, the dealiasing range would increase from 3 m to 30 m, but at a 25× increase in operating power for the same level of uncertainty. Thus, in practice dealiasing a TOF system simply by lowering the modulation frequency is accompanied by a very substantial performance penalty.
Ideally, dealiasing a TOF system would achieve the unambiguous range for a low modulation frequency, while providing the distance resolution for a high modulation frequency. But dealiasing in the presence of noise can be challenging, especially for high modulation frequencies, or for large unambiguous ranges.
What is needed for a phase-type TOF system is a method of dealiasing or disambiguating Z data results, especially in the presence of noise. Preferably dealiasing should function well in the presence of noise, even with high modulation frequencies or for large unambiguous ranges.
The present invention provides a method and system for dealiasing in phase-type TOF systems.